The Impact of Tissue Preparation on Salivary Gland Tumors Investigated by Fourier-Transform Infrared Microspectroscopy.

Due to the wide variety of benign and malignant salivary gland tumors, classification and malignant behavior determination based on histomorphological criteria can be difficult and sometimes impossible. Spectroscopical procedures can acquire molecular biological information without destroying the tissue within the measurement processes. Since several tissue preparation procedures exist, our study investigated the impact of these preparations on the chemical composition of healthy and tumorous salivary gland tissue by Fourier-transform infrared (FTIR) microspectroscopy. Sequential tissue cross-sections were prepared from native, formalin-fixed and formalin-fixed paraffin-embedded (FFPE) tissue and analyzed. The FFPE cross-sections were dewaxed and remeasured. By using principal component analysis (PCA) combined with a discriminant analysis (DA), robust models for the distinction of sample preparations were built individually for each parotid tissue type. As a result, the PCA-DA model evaluation showed a high similarity between native and formalin-fixed tissues based on their chemical composition. Thus, formalin-fixed tissues are highly representative of the native samples and facilitate a transfer from scientific laboratory analysis into the clinical routine due to their robust nature. Furthermore, the dewaxing of the cross-sections entails the loss of molecular information. Our study successfully demonstrated how FTIR microspectroscopy can be used as a powerful tool within existing clinical workflows.

Differentiation of Salivary Gland and Salivary Gland Tumor Tissue via Raman Imaging Combined with Multivariate Data Analysis.

Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.

Prediction of Honeydew Contaminations on Cotton Samples by In-Line UV Hyperspectral Imaging.

UV hyperspectral imaging (225 nm-410 nm) was used to identify and quantify the honeydew content of real cotton samples. Honeydew contamination causes losses of millions of dollars annually. This study presents the implementation and application of UV hyperspectral imaging as a non-destructive, high-resolution, and fast imaging modality. For this novel approach, a reference sample set, which consists of sugar and protein solutions that were adapted to honeydew, was set-up. In total, 21 samples with different amounts of added sugars/proteins were measured to calculate multivariate models at each pixel of a hyperspectral image to predict and classify the amount of sugar and honeydew. The principal component analysis models (PCA) enabled a general differentiation between different concentrations of sugar and honeydew. A partial least squares regression (PLS-R) model was built based on the cotton samples soaked in different sugar and protein concentrations. The result showed a reliable performance with R2cv = 0.80 and low RMSECV = 0.01 g for the validation. The PLS-R reference model was able to predict the honeydew content laterally resolved in grams on real cotton samples for each pixel with light, strong, and very strong honeydew contaminations. Therefore, inline UV hyperspectral imaging combined with chemometric models can be an effective tool in the future for the quality control of industrial processing of cotton fibers.

Comparison of Whiskbroom and Pushbroom darkfield elastic light scattering spectroscopic imaging for head and neck cancer identification in a mouse model.

The early detection of head and neck cancer is a prolonged challenging task. It requires a precise and accurate identification of tissue alterations as well as a distinct discrimination of cancerous from healthy tissue areas. A novel approach for this purpose uses microspectroscopic techniques with special focus on hyperspectral imaging (HSI) methods. Our proof-of-principle study presents the implementation and application of darkfield elastic light scattering spectroscopy (DF ELSS) as a non-destructive, high-resolution, and fast imaging modality to distinguish lingual healthy from altered tissue regions in a mouse model. The main aspect of our study deals with the comparison of two varying HSI detection principles, which are a point-by-point and line scanning imaging, and whether one might be more appropriate in differentiating several tissue types. Statistical models are formed by deploying a principal component analysis (PCA) with the Bayesian discriminant analysis (DA) on the elastic light scattering (ELS) spectra. Overall accuracy, sensitivity, and precision values of 98% are achieved for both models whereas the overall specificity results in 99%. An additional classification of model-unknown ELS spectra is performed. The predictions are verified with histopathological evaluations of identical HE-stained tissue areas to prove the model's capability of tissue distinction. In the context of our proof-of-principle study, we assess the Pushbroom PCA-DA model to be more suitable for tissue type differentiations and thus tissue classification. In addition to the HE-examination in head and neck cancer diagnosis, the usage of HSI-based statistical models might be conceivable in a daily clinical routine.

UV Hyperspectral Imaging as Process Analytical Tool for the Characterization of Oxide Layers and Copper States on Direct Bonded Copper.

Hyperspectral imaging and reflectance spectroscopy in the range from 200-380 nm were used to rapidly detect and characterize copper oxidation states and their layer thicknesses on direct bonded copper in a non-destructive way. Single-point UV reflectance spectroscopy, as a well-established method, was utilized to compare the quality of the hyperspectral imaging results. For the laterally resolved measurements of the copper surfaces an UV hyperspectral imaging setup based on a pushbroom imager was used. Six different types of direct bonded copper were studied. Each type had a different oxide layer thickness and was analyzed by depth profiling using X-ray photoelectron spectroscopy. In total, 28 samples were measured to develop multivariate models to characterize and predict the oxide layer thicknesses. The principal component analysis models (PCA) enabled a general differentiation between the sample types on the first two PCs with 100.0% and 96% explained variance for UV spectroscopy and hyperspectral imaging, respectively. Partial least squares regression (PLS-R) models showed reliable performance with R2c = 0.94 and 0.94 and RMSEC = 1.64 nm and 1.76 nm, respectively. The developed in-line prototype system combined with multivariate data modeling shows high potential for further development of this technique towards real large-scale processes.

Exploring the hidden depth by confocal Raman experiments with variable objective aperture and magnification.

The article analyzes experimentally and theoretically the influence of microscope parameters on the pinhole-assisted Raman depth profiles in uniform and composite refractive media. The main objective is the reliable mapping of deep sample regions. The easiest to interpret results are found with low magnification, low aperture, and small pinholes. Here, the intensities and shapes of the Raman signals are independent of the location of the emitter relative to the sample surface. Theoretically, the results can be well described with a simple analytical equation containing the axial depth resolution of the microscope and the position of the emitter. The lower determinable object size is limited to 2-4 µm. If sub-micrometer resolution is desired, high magnification, mostly combined with high aperture, becomes necessary. The signal intensities and shapes depend now in refractive media on the position relative to the sample surface. This aspect is investigated on a number of uniform and stacked polymer layers, 2-160 µm thick, with the best available transparency. The experimental depth profiles are numerically fitted with excellent accuracy by inserting a Gaussian excitation beam of variable waist and fill fraction through the focusing lens area, and by treating the Raman emission with geometric optics as spontaneous isotropic process through the lens and the variable pinhole, respectively. The intersectional area of these two solid angles yields the leading factor in understanding confocal (pinhole-assisted) Raman depth profiles. Spearfishing is a well-known example of the effects of refraction at the boundary between two index-mismatched media. The object Greal is seen, due to refraction, as Gvir from the angle ß (without knowing the depth position). The real position is obtained under the angle α. In a microscope (see inset), index mismatch deforms the image point of Greal into an image line. The pinhole substantially reduces deformations and allows the determination of the position of the point emitter G. (Cartoon designed by Sofia Anker).

Characterization of Pharmaceutical Tablets Using UV Hyperspectral Imaging as a Rapid In-Line Analysis Tool.

A laboratory prototype for hyperspectral imaging in ultra-violet (UV) region from 225 to 400 nm was developed and used to rapidly characterize active pharmaceutical ingredients (API) in tablets. The APIs are ibuprofen (IBU), acetylsalicylic acid (ASA) and paracetamol (PAR). Two sample sets were used for a comparison purpose. Sample set one comprises tablets of 100% API and sample set two consists of commercially available painkiller tablets. Reference measurements were performed on the pure APIs in liquid solutions (transmission) and in solid phase (reflection) using a commercial UV spectrometer. The spectroscopic part of the prototype is based on a pushbroom imager that contains a spectrograph and charge-coupled device (CCD) camera. The tablets were scanned on a conveyor belt that is positioned inside a tunnel made of polytetrafluoroethylene (PTFE) in order to increase the homogeneity of illumination at the sample position. Principal component analysis (PCA) was used to differentiate the hyperspectral data of the drug samples. The first two PCs are sufficient to completely separate all samples. The rugged design of the prototype opens new possibilities for further development of this technique towards real large-scale application.

Direct optical detection of cell density and viability of mammalian cells by means of UV/VIS spectroscopy.

The critical process parameters cell density and viability during mammalian cell cultivation are assessed by UV/VIS spectroscopy in combination with multivariate data analytical methods. This direct optical detection technique uses a commercial optical probe to acquire spectra in a label-free way without signal enhancement. For the cultivation, an inverse cultivation protocol is applied, which simulates the exponential growth phase by exponentially replacing cells and metabolites of a growing Chinese hamster ovary cell batch with fresh medium. For the simulation of the death phase, a batch of growing cells is progressively replaced by a batch with completely starved cells. Thus, the most important parts of an industrial batch cultivation are easily imitated. The cell viability was determined by the well-established method partial least squares regression (PLS). To further improve process knowledge, the viability has been determined from the spectra based on a multivariate curve resolution (MCR) model. With this approach, the progress of the cultivations can be continuously monitored solely based on an UV/VIS sensor. Thus, the monitoring of critical process parameters is possible inline within a mammalian cell cultivation process, especially the viable cell density. In addition, the beginning of cell death can be detected by this method which allows us to determine the cell viability with acceptable error. The combination of inline UV/VIS spectroscopy with multivariate curve resolution generates additional process knowledge complementary to PLS and is considered a suitable process analytical tool for monitoring industrial cultivation processes.

Pigmentation of White, Brown, and Green Chicken Eggshells Analyzed by Reflectance, Transmittance, and Fluorescence Spectroscopy.

We report on the reflectance, transmittance and fluorescence spectra (λ=200-1200 nm) of four types of chicken eggshells (white, brown, light green, dark green) measured in situ without pretreatment and after ablation of 20-100 µm of the outer shell regions. The color pigment protoporphyrin IX (PPIX) is embedded in the protein phase of all four shell types as highly fluorescent monomers, in the white and light green shells additionally as non-fluorescent dimers, and in the brown and dark green shells mainly as non-fluorescent poly-aggregates. The green shell colors are formed from an approximately equimolar mixture of PPIX and biliverdin. The axial distribution of protein and colorpigments were evaluated from the combined reflectances of both the outer and inner shell surfaces, as well as from the transmittances. For the data generation we used the radiative transfer model in the random walk and Kubelka-Munk approaches.

Elastic and inelastic light scattering spectroscopy and its possible use for label-free brain tumor typing.

This paper presents an approach for label-free brain tumor tissue typing. For this application, our dual modality microspectroscopy system combines inelastic Raman scattering spectroscopy and Mie elastic light scattering spectroscopy. The system enables marker-free biomedical diagnostics and records both the chemical and morphologic changes of tissues on a cellular and subcellular level. The system setup is described and the suitability for measuring morphologic features is investigated. Graphical Abstract Bimodal approach for label-free brain tumor typing. Elastic and inelastic light scattering spectra are collected laterally resolved in one measurement setup. The spectra are investigated by multivariate data analysis for assigning the tissues to specific WHO grades according to their malignancy.

Process analytical techniques for hot-melt extrusion and their application to amorphous solid dispersions.

Newly developed active pharmaceutical ingredients (APIs) are often poorly soluble in water. As a result the bioavailability of the API in the human body is reduced. One approach to overcome this restriction is the formulation of amorphous solid dispersions (ASDs), e.g., by hot-melt extrusion (HME). Thus, the poorly soluble crystalline form of the API is transferred into a more soluble amorphous form. To reach this aim in HME, the APIs are embedded in a polymer matrix. The resulting amorphous solid dispersions may contain small amounts of residual crystallinity and have the tendency to recrystallize. For the controlled release of the API in the final drug product the amount of crystallinity has to be known. This review assesses the available analytical methods that have been recently used for the characterization of ASDs and the quantification of crystalline API content. Well-established techniques like near- and mid-infrared spectroscopy (NIR and MIR, respectively), Raman spectroscopy, and emerging ones like UV/VIS, terahertz, and ultrasonic spectroscopy are considered in detail. Furthermore, their advantages and limitations are discussed with regard to general practical applicability as process analytical technology (PAT) tools in industrial manufacturing. The review focuses on spectroscopic methods which have been proven as most suitable for in-line and on-line process analytics. Further aspects are spectroscopic techniques that have been or could be integrated into an extruder.

Hyperspectral backscatter imaging: a label-free approach to cytogenetics.

Current techniques for chromosome analysis need to be improved for rapid, economical identification of complex chromosomal defects by sensitive and selective visualisation. In this paper, we present a straightforward method for characterising unstained human metaphase chromosomes. Backscatter imaging in a dark-field setup combined with visible and short near-infrared spectroscopy is used to monitor morphological differences in the distribution of the chromosomal fine structure in human metaphase chromosomes. The reasons for the scattering centres in the fine structure are explained. Changes in the scattering centres during preparation of the metaphases are discussed. FDTD simulations are presented to substantiate the experimental findings. We show that local scattering features consisting of underlying spectral modulations of higher frequencies associated with a high variety of densely packed chromatin can be represented by their scatter profiles even on a sub-microscopic level. The result is independent of the chromosome preparation and structure size. This analytical method constitutes a rapid, cost-effective and label-free cytogenetic technique which can be used in a standard light microscope. Graphical abstract Hyperspectral backscatter imaging for label-free characterization.

Quantitative Raman spectroscopy in turbid matter: reflection or transmission mode?

Raman intensities from reflection (X(R)) and transmission (X(T)) setups are compared by calculations based on random walk and analytical approaches with respect to sample thickness, absorption, and scattering. Experiments incorporating strongly scattering organic polymer layers and powder tablets of pharmaceutical ingredients validate the theoretical findings. For nonabsorbing layers, the Raman reflection and transmission intensities rise steadily with the layer thickness, starting for very thin layers with the ratio X(T)/X(R) = 1 and approaching for thick layers, a lower limit of X(T)/X(R) = 0.5. This result is completely different from the primary irradiation where the ratio of transmittance/reflectance decays hyperbolically with the layer thickness to zero. In absorbing materials, X R saturates at levels that depend strongly on the absorption and scattering coefficients. X T passes through a maximum and decreases then exponentially with increasing layer thickness to zero. From the calculated radial intensity spreads, it follows that quantitative transmission Raman spectroscopy requires diameters of the detected sample areas be about six times larger than the sample thickness. In stratified systems, Raman transmission allows deep probing even of small quantities in buried layers. In double layers, the information is independent from the side of the measurements. In triple layers simulating coated tablets, the information of X T originates mainly from the center of the bulk material whereas X R highlights the irradiated boundary region. However, if the stratified sample is measured in a Raman reflection setup in front of a white diffusely reflecting surface, it is possible to monitor the whole depth of a multiple scattering sample with equal statistical weight. This may be a favorable approach for inline Raman spectroscopy in process analytical technology.

Effects of storage conditions on furocoumarin levels in intact, chopped, or homogenized parsnips.

Furocoumarins represent a family of natural food constituents with phototoxic and photomutagenic properties. They are found mainly in plants belonging to the Rutaceae and Umbilliferae such as celery, carrots, and parsnips. Parsnips (Pastinaca sativa L.) have become more and more popular as a vegetable, e.g., as a constituent of or ingredient in baby food. Previous work has shown that microbial infection of parsnip roots can result in a dramatic increase in furocoumarin levels. In this study, freshly harvested parsnips were stored as whole roots, pieces (cubes), or homogenate at +4 degrees C or -18 degrees C over various time periods under standard conditions. It was found that furocoumarin concentrations (sum of five furocoumarins: angelicin, isopimpinellin, 5-methoxypsoralen, 8-methoxypsoralen, and psoralen) in freshly harvested parsnips, analyzed by HPLC after extraction with diethyl ether and sequential solid phase (reversed-phase and silica) extraction, was generally lower than 2.5 mg/kg, and storage of parsnips in any form investigated at -18 degrees C over up to 50 days did not lead to a marked increase in furocoumarin levels. In contrast, storage of whole parsnips, but not of cubes or homogenate, at +4 degrees C resulted in a marked biphasic increase of furocoumarin concentrations after 7 and 38 days of storage up to levels of about 40 mg/kg. A dramatic increase in furocoumarin concentrations up to 566 mg/kg was observed when whole parsnips obtained from the market were kept at room temperature over 53 days, resulting in a visible microbial (mold) infection. Baby food products from the German market containing parsnips as an ingredient or constituent showed furocoumarin levels < or =0.41 mg/kg, suggesting that properly stored roots/preparations have been used. It is recommended that, after harvesting, parsnips be kept at -18 degrees C or under other conditions that prevent microbial infections.